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Smart city article details

Title	A Secure And Efficient Blockchain-Based Framework For Smart Cities Using Physics-Informed Neural Networks
ID_Doc	4450
Authors	Gandhi M.A.; Narkhede A.D.; Alleema N.N.; Indumathi M.P.; Sundrani D.; Sasikala R.
Year	2025
Published	EAI Endorsed Transactions on Internet of Things, 11
DOI	http://dx.doi.org/10.4108/eetiot.7740
Abstract	The massive scale and extensive implementation of the Internet of Things (IoT) makes it difficult to provide secure and private communications over it. Privacy and decentralisation have been made easier using blockchain technology. Unfortunately, these solutions aren't practical for the majority of IoT uses because of how much time and computing power they require. Secure and private IoT that makes efficient use of available resources is proposed in this study. With the use of Physics Informed Neural Networks, the technique takes advantage of the computing power available in IoT settings like smart cities. This solution examines the reliability of the blockchain-based Smart Cities Architecture with respect to accessibility, privacy, and integrity. When weighed against the security and privacy advantages our system offers, our simulation findings reveal that the overheads (distribution, processing time, and energy usage) are negligible. © 2025 Mohd Asif Gandhi et al.
Author Keywords	Block Chain; Feature Selection; Kernel Principal Component Analysis (KPCA); Neural Networks; Normalization; Physics Informed Neural Networks; Privacy-Preserving and Secure Framework (PPSF); Smart Cities (SC)

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